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Abstract The gold standard to measure arterial health is vasodilation in response to nitric oxide. Vasodilation is generally measured via pressure myography of arteries isolated from animal models. However, animal arteries can be difficult to obtain and may have limited relevance to human physiology. It is, therefore, critical to engineer human cell-based arterial models capable of contraction. Vascular smooth muscle cells (SMCs) must be circumferentially aligned around the vessel lumen to contract the vessel, which is challenging to achieve in a soft blood vessel model. In this study, we used gelatin microribbons to circumferentially align SMCs inside a hydrogel channel. To accomplish this, we created tunable gelatin microribbons of varying stiffnesses and thicknesses and assessed how SMCs aligned along them. We then wrapped soft, thick microribbons around a needle and encapsulated them in a gelatin methacryloyl hydrogel, forming a microribbon-lined channel. Finally, we seeded SMCs inside the channel and showed that they adhered best to fibronectin and circumferentially aligned in response to the microribbons. Together, these data show that tunable gelatin microribbons can be used to circumferentially align SMCs inside a channel. This technique can be used to create a human artery-on-a-chip to assess vasodilation via pressure myography, as well as to align other cell types for 3Din vitromodels. 

Human primary (hpBMEC) and induced pluripotent stem cell (iPSC)-derived brain microvascular endothelial-like cells (hiBMEC) are interchangeably used in blood-brain barrier models to study neurological diseases and drug delivery. Both hpBMEC and hiBMEC use glutamine as a source of carbon and nitrogen to produce metabolites and build proteins essential to cell function and communication. We used metabolomic, transcriptomic, and computational methods to examine how hpBMEC and hiBMEC metabolize glutamine, which may impact their utility in modeling the blood-brain barrier. We found that glutamine metabolism was systemically different between the two cell types. hpBMEC had a higher metabolic rate and produced more glutamate and GABA, while hiBMEC rerouted glutamine to produce more glutathione, fatty acids, and asparagine. Higher glutathione production in hiBMEC correlated with higher oxidative stress compared to hpBMEC. α-ketoglutarate (α-KG) supplementation increased glutamate secretion from hiBMEC to match that of hpBMEC; however, α-KG also decreased hiBMEC glycolytic rate. These fundamental metabolic differences between BMEC types may impactin vitroblood-brain barrier model function, particularly communication between BMEC and surrounding cells, and emphasize the importance of evaluating the metabolic impacts of iPSC-derived cells in disease models. 

The human body represents a collection of interacting systems that range in scale from nanometers to meters. Investigations from a systems perspective focus on how the parts work together to enact changes across spatial scales, and further our understanding of how systems function and fail. Here, we highlight systems approaches presented at the 2022 Summer Biomechanics, Bio-engineering, and Biotransport Conference in the areas of solid mechanics; fluid mechanics; tissue and cellular engineering; biotransport; and design, dynamics, and rehabilitation; and biomechanics education. Systems approaches are yielding new insights into human biology by leveraging state-of-the-art tools, which could ultimately lead to more informed design of therapies and medical devices for preventing and treating disease as well as rehabilitating patients using strategies that are uniquely optimized for each patient. Educational approaches can also be designed to foster a foundation of systems-level thinking. 

Cell metabolism represents the coordinated changes in genes, proteins, and metabolites that occur in health and disease. The metabolic fluxome, which includes both intracellular and extracellular metabolic reaction rates (fluxes), therefore provides a powerful, integrated description of cellular phenotype. However, intracellular fluxes cannot be directly measured. Instead, flux quantification requires sophisticated mathematical and computational analysis of data from isotope labeling experiments. In this review, we describe isotope-assisted metabolic flux analysis (iMFA), a rigorous computational approach to fluxome quantification that integrates metabolic network models and experimental data to generate quantitative metabolic flux maps. We highlight practical considerations for implementing iMFA in mammalian models, as well as iMFA applications in in vitro and in vivo studies of physiology and disease. Finally, we identify promising new frontiers in iMFA which may enable us to fully unlock the potential of iMFA in biomedical research. 

Abstract Glucose transport from the blood into the brain is tightly regulated by brain microvascular endothelial cells (BMEC), which also use glucose as their primary energy source. To study how BMEC glucose transport contributes to cerebral glucose hypometabolism in diseases such as Alzheimer’s disease, it is essential to understand how these cells metabolize glucose. Human primary BMEC (hpBMEC) can be used for BMEC metabolism studies; however, they have poor barrier function and may not recapitulate in vivo BMEC function. iPSC-derived BMEC-like cells (hiBMEC) are readily available and have good barrier function but may have an underlying epithelial signature. In this study, we examined differences between hpBMEC and hiBMEC glucose metabolism using a combination of dynamic metabolic measurements, metabolic mass spectrometry, RNA sequencing, and Western blots. hiBMEC had decreased glycolytic flux relative to hpBMEC, and the overall metabolomes and metabolic enzyme levels were different between the two cell types. However, hpBMEC and hiBMEC had similar glucose metabolism, including nearly identical glucose labeled fractions of glycolytic and TCA cycle metabolites. Treatment with astrocyte conditioned media and high glucose increased glycolysis in both hpBMEC and hiBMEC, though hpBMEC decreased glycolysis in response to fluvastatin while hiBMEC did not. Together, these results suggest that hiBMEC can be used to model cerebral vascular glucose metabolism, which expands their use beyond barrier models. 

The 2018 BMES Cellular and Molecular Bioengineering (CMBE) Conference was organized around the theme of Discovering the Keys: Transformative and Translational Mechanobiology. The conference programming included a panel discussion on Translating Mechanobiology to the Clinic. The goal of the panel was to initiate a dialogue and share pearls of wisdom from participants’ successes and failures in academia and in industry toward translating scientific discoveries in mechanobiology to technology products in the market or toward devices or drugs that impact clinical care. This commentary reviews the major themes and questions discussed during the panel, including defining translational research and how it applies to mechanobiology, the current landscape in translational mechanobiology, the process for translating mechanobiology research, challenges in translating mechanobiology research, and unique opportunities in translating mechanobiology research.